Data
analcatdata_reviewer

analcatdata_reviewer

active ARFF Publicly available Visibility: public Uploaded 28-09-2014 by Joaquin Vanschoren
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Author: Source: Unknown - Date unknown Please cite: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this README file. Each data set is given in comma-delimited ASCII (.csv) form, and Microsoft Excel (.xls) form. NOTICE: These data sets may be used freely for scientific, educational and/or noncommercial purposes, provided suitable acknowledgment is given (by citing the above-named reference). Further details concerning the book, including information on statistical software (including sample S-PLUS/R and SAS code), are available at the web site http://www.stern.nyu.edu/~jsimonof/AnalCatData Information about the dataset CLASSTYPE: nominal CLASSINDEX: none specific Note: Quotes, Single-Quotes and Backslashes were removed, Blanks replaced with Underscores

9 features

Roger_Ebert (target)nominal3 unique values
141 missing
Film (ignore)nominal379 unique values
0 missing
Jeffrey_Lyonsnominal3 unique values
105 missing
Michael_Medvednominal3 unique values
206 missing
Rex_Reednominal3 unique values
189 missing
Gene_Shalitnominal3 unique values
318 missing
Joel_Siegelnominal3 unique values
210 missing
Gene_Siskelnominal3 unique values
199 missing
Peter_Traversnominal3 unique values
50 missing

107 properties

379
Number of instances (rows) of the dataset.
9
Number of attributes (columns) of the dataset.
4
Number of distinct values of the target attribute (if it is nominal).
1418
Number of missing values in the dataset.
365
Number of instances with at least one value missing.
0
Number of numeric attributes.
9
Number of nominal attributes.
23.17
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
0.02
First quartile of mutual information between the nominal attributes and the target attribute.
0.48
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.18
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
3
Average number of distinct values among the attributes of the nominal type.
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.46
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Mean skewness among attributes of the numeric type.
First quartile of standard deviation of attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.48
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.09
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
Mean standard deviation of attributes of the numeric type.
1.15
Second quartile (Median) of entropy among attributes.
0.48
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.4
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
37.2
Percentage of instances belonging to the most frequent class.
0.68
Minimal entropy among attributes.
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
1.44
Entropy of the target attribute values.
0.34
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
141
Number of instances belonging to the most frequent class.
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
1.55
Maximum entropy among attributes.
Minimum of means among attributes of the numeric type.
0.02
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.48
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.43
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum kurtosis among attributes of the numeric type.
0.01
Minimal mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum of means among attributes of the numeric type.
3
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.02
Number of attributes divided by the number of instances.
0.19
Maximum mutual information between the nominal attributes and the target attribute.
Minimum skewness among attributes of the numeric type.
96.31
Percentage of instances having missing values.
1.36
Third quartile of entropy among attributes.
0.45
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
29.32
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
3
The maximum number of distinct values among attributes of the nominal type.
Minimum standard deviation of attributes of the numeric type.
41.57
Percentage of missing values.
Third quartile of kurtosis among attributes of the numeric type.
0.16
Average class difference between consecutive instances.
0.18
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Maximum skewness among attributes of the numeric type.
14.25
Percentage of instances belonging to the least frequent class.
0
Percentage of numeric attributes.
Third quartile of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.46
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Maximum standard deviation of attributes of the numeric type.
54
Number of instances belonging to the least frequent class.
100
Percentage of nominal attributes.
0.05
Third quartile of mutual information between the nominal attributes and the target attribute.
0.48
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.45
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.09
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.19
Average entropy of the attributes.
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.13
First quartile of entropy among attributes.
Third quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.18
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Mean kurtosis among attributes of the numeric type.
0.38
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of kurtosis among attributes of the numeric type.
Third quartile of standard deviation of attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.46
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Mean of means among attributes of the numeric type.
0.05
Average mutual information between the nominal attributes and the target attribute.
0.37
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.48
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.45
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.09
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

4 tasks

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Roger_Ebert
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Roger_Ebert
Define a new task